Overview

Dataset statistics

Number of variables47
Number of observations152
Missing cells1518
Missing cells (%)21.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory60.1 KiB
Average record size in memory404.9 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric6
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-19285/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
건물소유구분명 is highly imbalanced (53.9%)Imbalance
여성종사자수 is highly imbalanced (50.5%)Imbalance
남성종사자수 is highly imbalanced (58.7%)Imbalance
인허가취소일자 has 152 (100.0%) missing valuesMissing
폐업일자 has 49 (32.2%) missing valuesMissing
휴업시작일자 has 152 (100.0%) missing valuesMissing
휴업종료일자 has 152 (100.0%) missing valuesMissing
재개업일자 has 152 (100.0%) missing valuesMissing
전화번호 has 47 (30.9%) missing valuesMissing
도로명주소 has 40 (26.3%) missing valuesMissing
도로명우편번호 has 41 (27.0%) missing valuesMissing
좌표정보(X) has 2 (1.3%) missing valuesMissing
좌표정보(Y) has 2 (1.3%) missing valuesMissing
건물지상층수 has 47 (30.9%) missing valuesMissing
사용시작지상층 has 74 (48.7%) missing valuesMissing
사용끝지상층 has 89 (58.6%) missing valuesMissing
발한실여부 has 34 (22.4%) missing valuesMissing
조건부허가신고사유 has 152 (100.0%) missing valuesMissing
조건부허가시작일자 has 152 (100.0%) missing valuesMissing
조건부허가종료일자 has 152 (100.0%) missing valuesMissing
다중이용업소여부 has 28 (18.4%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 66 (43.4%) zerosZeros
사용시작지상층 has 22 (14.5%) zerosZeros
사용끝지상층 has 14 (9.2%) zerosZeros

Reproduction

Analysis started2024-04-29 19:52:32.578556
Analysis finished2024-04-29 19:52:33.482340
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3080000
152 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 152
100.0%

Length

2024-04-30T04:52:33.549577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:33.625740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 152
100.0%

관리번호
Text

UNIQUE 

Distinct152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:52:33.770055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3344
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)100.0%

Sample

1st row3080000-206-1992-02093
2nd row3080000-206-1995-02094
3rd row3080000-206-1995-02095
4th row3080000-206-1995-02096
5th row3080000-206-1995-02097
ValueCountFrequency (%)
3080000-206-1992-02093 1
 
0.7%
3080000-206-2015-00001 1
 
0.7%
3080000-206-2016-00009 1
 
0.7%
3080000-206-2013-00005 1
 
0.7%
3080000-206-2013-00006 1
 
0.7%
3080000-206-2014-00001 1
 
0.7%
3080000-206-2014-00002 1
 
0.7%
3080000-206-2014-00003 1
 
0.7%
3080000-206-2014-00004 1
 
0.7%
3080000-206-2016-00002 1
 
0.7%
Other values (142) 142
93.4%
2024-04-30T04:52:34.066314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1696
50.7%
- 456
 
13.6%
2 375
 
11.2%
3 193
 
5.8%
6 182
 
5.4%
8 170
 
5.1%
1 120
 
3.6%
9 64
 
1.9%
4 34
 
1.0%
5 29
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2888
86.4%
Dash Punctuation 456
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1696
58.7%
2 375
 
13.0%
3 193
 
6.7%
6 182
 
6.3%
8 170
 
5.9%
1 120
 
4.2%
9 64
 
2.2%
4 34
 
1.2%
5 29
 
1.0%
7 25
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 456
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3344
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1696
50.7%
- 456
 
13.6%
2 375
 
11.2%
3 193
 
5.8%
6 182
 
5.4%
8 170
 
5.1%
1 120
 
3.6%
9 64
 
1.9%
4 34
 
1.0%
5 29
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1696
50.7%
- 456
 
13.6%
2 375
 
11.2%
3 193
 
5.8%
6 182
 
5.4%
8 170
 
5.1%
1 120
 
3.6%
9 64
 
1.9%
4 34
 
1.0%
5 29
 
0.9%
Distinct148
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1992-02-21 00:00:00
Maximum2024-02-29 00:00:00
2024-04-30T04:52:34.191762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:52:34.309545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3
103 
1
49 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 103
67.8%
1 49
32.2%

Length

2024-04-30T04:52:34.418119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:34.501379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 103
67.8%
1 49
32.2%

영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
103 
영업/정상
49 

Length

Max length5
Median length2
Mean length2.9671053
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 103
67.8%
영업/정상 49
32.2%

Length

2024-04-30T04:52:34.606717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:34.713791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 103
67.8%
영업/정상 49
32.2%
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2
103 
1
49 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 103
67.8%
1 49
32.2%

Length

2024-04-30T04:52:34.819380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:34.906747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 103
67.8%
1 49
32.2%
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
103 
영업
49 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 103
67.8%
영업 49
32.2%

Length

2024-04-30T04:52:35.010088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:35.092478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 103
67.8%
영업 49
32.2%

폐업일자
Date

MISSING 

Distinct97
Distinct (%)94.2%
Missing49
Missing (%)32.2%
Memory size1.3 KiB
Minimum1996-10-30 00:00:00
Maximum2024-02-21 00:00:00
2024-04-30T04:52:35.182013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:52:35.297420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Text

MISSING 

Distinct101
Distinct (%)96.2%
Missing47
Missing (%)30.9%
Memory size1.3 KiB
2024-04-30T04:52:35.532605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.914286
Min length7

Characters and Unicode

Total characters1146
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)92.4%

Sample

1st row02 9989100
2nd row02 9849840
3rd row02 9336856
4th row02 9972391
5th row02 9888384
ValueCountFrequency (%)
02 89
37.4%
070 5
 
2.1%
906 4
 
1.7%
990 2
 
0.8%
985 2
 
0.8%
9992922 2
 
0.8%
993 2
 
0.8%
992 2
 
0.8%
982 2
 
0.8%
9990797 2
 
0.8%
Other values (124) 126
52.9%
2024-04-30T04:52:35.882935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
190
16.6%
0 183
16.0%
2 169
14.7%
9 163
14.2%
4 74
 
6.5%
8 73
 
6.4%
7 70
 
6.1%
1 64
 
5.6%
5 58
 
5.1%
3 52
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 956
83.4%
Space Separator 190
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 183
19.1%
2 169
17.7%
9 163
17.1%
4 74
7.7%
8 73
 
7.6%
7 70
 
7.3%
1 64
 
6.7%
5 58
 
6.1%
3 52
 
5.4%
6 50
 
5.2%
Space Separator
ValueCountFrequency (%)
190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1146
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
190
16.6%
0 183
16.0%
2 169
14.7%
9 163
14.2%
4 74
 
6.5%
8 73
 
6.4%
7 70
 
6.1%
1 64
 
5.6%
5 58
 
5.1%
3 52
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
190
16.6%
0 183
16.0%
2 169
14.7%
9 163
14.2%
4 74
 
6.5%
8 73
 
6.4%
7 70
 
6.1%
1 64
 
5.6%
5 58
 
5.1%
3 52
 
4.5%
Distinct99
Distinct (%)65.6%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2024-04-30T04:52:36.120557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8940397
Min length3

Characters and Unicode

Total characters739
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)55.6%

Sample

1st row.00
2nd row85.00
3rd row.00
4th row110.00
5th row.00
ValueCountFrequency (%)
00 17
 
11.3%
36.90 9
 
6.0%
33.00 7
 
4.6%
45.00 4
 
2.6%
30.00 4
 
2.6%
10.00 4
 
2.6%
66.00 4
 
2.6%
3.30 4
 
2.6%
32.00 2
 
1.3%
39.60 2
 
1.3%
Other values (89) 94
62.3%
2024-04-30T04:52:36.477678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 221
29.9%
. 151
20.4%
3 62
 
8.4%
1 54
 
7.3%
2 51
 
6.9%
6 43
 
5.8%
4 43
 
5.8%
9 30
 
4.1%
5 29
 
3.9%
8 27
 
3.7%
Other values (2) 28
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 587
79.4%
Other Punctuation 152
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 221
37.6%
3 62
 
10.6%
1 54
 
9.2%
2 51
 
8.7%
6 43
 
7.3%
4 43
 
7.3%
9 30
 
5.1%
5 29
 
4.9%
8 27
 
4.6%
7 27
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 151
99.3%
, 1
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 739
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 221
29.9%
. 151
20.4%
3 62
 
8.4%
1 54
 
7.3%
2 51
 
6.9%
6 43
 
5.8%
4 43
 
5.8%
9 30
 
4.1%
5 29
 
3.9%
8 27
 
3.7%
Other values (2) 28
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 739
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 221
29.9%
. 151
20.4%
3 62
 
8.4%
1 54
 
7.3%
2 51
 
6.9%
6 43
 
5.8%
4 43
 
5.8%
9 30
 
4.1%
5 29
 
3.9%
8 27
 
3.7%
Other values (2) 28
 
3.8%
Distinct59
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:52:36.667181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1381579
Min length6

Characters and Unicode

Total characters933
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)21.7%

Sample

1st row142877
2nd row142803
3rd row142867
4th row142864
5th row142886
ValueCountFrequency (%)
142877 12
 
7.9%
142803 12
 
7.9%
142867 11
 
7.2%
142872 8
 
5.3%
142815 7
 
4.6%
142070 7
 
4.6%
142878 6
 
3.9%
142864 5
 
3.3%
142809 5
 
3.3%
142874 4
 
2.6%
Other values (49) 75
49.3%
2024-04-30T04:52:36.955667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 188
20.2%
2 173
18.5%
4 170
18.2%
8 157
16.8%
7 81
8.7%
0 54
 
5.8%
6 40
 
4.3%
3 21
 
2.3%
- 21
 
2.3%
5 14
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 912
97.7%
Dash Punctuation 21
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 188
20.6%
2 173
19.0%
4 170
18.6%
8 157
17.2%
7 81
8.9%
0 54
 
5.9%
6 40
 
4.4%
3 21
 
2.3%
5 14
 
1.5%
9 14
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 933
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 188
20.2%
2 173
18.5%
4 170
18.2%
8 157
16.8%
7 81
8.7%
0 54
 
5.8%
6 40
 
4.3%
3 21
 
2.3%
- 21
 
2.3%
5 14
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 933
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 188
20.2%
2 173
18.5%
4 170
18.2%
8 157
16.8%
7 81
8.7%
0 54
 
5.8%
6 40
 
4.3%
3 21
 
2.3%
- 21
 
2.3%
5 14
 
1.5%
Distinct147
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:52:37.212177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length26
Min length18

Characters and Unicode

Total characters3952
Distinct characters134
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)93.4%

Sample

1st row서울특별시 강북구 수유동 205-0 수유벽산 B동상가 110호
2nd row서울특별시 강북구 미아동 189-14 (도봉로 258)
3rd row서울특별시 강북구 번동 446-13
4th row서울특별시 강북구 번동 415-19 (오패산길 400)
5th row서울특별시 강북구 수유동 472-510
ValueCountFrequency (%)
서울특별시 152
19.3%
강북구 152
19.3%
미아동 59
 
7.5%
수유동 58
 
7.4%
번동 33
 
4.2%
446-13 13
 
1.6%
1층 10
 
1.3%
2층 8
 
1.0%
가든타워 6
 
0.8%
도봉로 6
 
0.8%
Other values (243) 292
37.0%
2024-04-30T04:52:37.608856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
745
18.9%
1 184
 
4.7%
170
 
4.3%
154
 
3.9%
153
 
3.9%
152
 
3.8%
152
 
3.8%
152
 
3.8%
152
 
3.8%
152
 
3.8%
Other values (124) 1786
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2078
52.6%
Decimal Number 909
23.0%
Space Separator 745
 
18.9%
Dash Punctuation 146
 
3.7%
Open Punctuation 26
 
0.7%
Close Punctuation 26
 
0.7%
Other Punctuation 9
 
0.2%
Uppercase Letter 9
 
0.2%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
170
 
8.2%
154
 
7.4%
153
 
7.4%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
74
 
3.6%
Other values (97) 615
29.6%
Decimal Number
ValueCountFrequency (%)
1 184
20.2%
3 130
14.3%
2 117
12.9%
4 108
11.9%
0 93
10.2%
6 69
 
7.6%
7 59
 
6.5%
5 57
 
6.3%
8 55
 
6.1%
9 37
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
K 1
 
11.1%
T 1
 
11.1%
L 1
 
11.1%
H 1
 
11.1%
E 1
 
11.1%
A 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
s 1
25.0%
u 1
25.0%
o 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
. 1
 
11.1%
Space Separator
ValueCountFrequency (%)
745
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2078
52.6%
Common 1861
47.1%
Latin 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
170
 
8.2%
154
 
7.4%
153
 
7.4%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
74
 
3.6%
Other values (97) 615
29.6%
Common
ValueCountFrequency (%)
745
40.0%
1 184
 
9.9%
- 146
 
7.8%
3 130
 
7.0%
2 117
 
6.3%
4 108
 
5.8%
0 93
 
5.0%
6 69
 
3.7%
7 59
 
3.2%
5 57
 
3.1%
Other values (6) 153
 
8.2%
Latin
ValueCountFrequency (%)
B 3
23.1%
K 1
 
7.7%
T 1
 
7.7%
L 1
 
7.7%
e 1
 
7.7%
s 1
 
7.7%
u 1
 
7.7%
o 1
 
7.7%
H 1
 
7.7%
E 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2078
52.6%
ASCII 1874
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
745
39.8%
1 184
 
9.8%
- 146
 
7.8%
3 130
 
6.9%
2 117
 
6.2%
4 108
 
5.8%
0 93
 
5.0%
6 69
 
3.7%
7 59
 
3.1%
5 57
 
3.0%
Other values (17) 166
 
8.9%
Hangul
ValueCountFrequency (%)
170
 
8.2%
154
 
7.4%
153
 
7.4%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
152
 
7.3%
74
 
3.6%
Other values (97) 615
29.6%

도로명주소
Text

MISSING 

Distinct112
Distinct (%)100.0%
Missing40
Missing (%)26.3%
Memory size1.3 KiB
2024-04-30T04:52:37.888100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length40
Mean length32.964286
Min length23

Characters and Unicode

Total characters3692
Distinct characters139
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)100.0%

Sample

1st row서울특별시 강북구 오패산로 396-1 (번동,(오패산길 400))
2nd row서울특별시 강북구 도봉로 328, 1319호 (번동, 가든타워)
3rd row서울특별시 강북구 도봉로 260 (미아동, 403호, 운산빌딩)
4th row서울특별시 강북구 도봉로 188, 삼성생명빌딩 지하1층 (미아동)
5th row서울특별시 강북구 노해로23길 138 (수유동,(영단길 90))
ValueCountFrequency (%)
서울특별시 112
 
15.4%
강북구 112
 
15.4%
미아동 43
 
5.9%
수유동 35
 
4.8%
도봉로 27
 
3.7%
1층 19
 
2.6%
번동 17
 
2.3%
2층 12
 
1.6%
328 12
 
1.6%
3층 10
 
1.4%
Other values (236) 330
45.3%
2024-04-30T04:52:38.292858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
617
 
16.7%
1 157
 
4.3%
125
 
3.4%
, 123
 
3.3%
( 122
 
3.3%
) 122
 
3.3%
115
 
3.1%
114
 
3.1%
113
 
3.1%
112
 
3.0%
Other values (129) 1972
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2017
54.6%
Decimal Number 656
 
17.8%
Space Separator 617
 
16.7%
Other Punctuation 125
 
3.4%
Open Punctuation 122
 
3.3%
Close Punctuation 122
 
3.3%
Dash Punctuation 20
 
0.5%
Uppercase Letter 9
 
0.2%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
125
 
6.2%
115
 
5.7%
114
 
5.7%
113
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
Other values (101) 878
43.5%
Decimal Number
ValueCountFrequency (%)
1 157
23.9%
2 89
13.6%
4 78
11.9%
3 72
11.0%
0 69
10.5%
8 45
 
6.9%
9 38
 
5.8%
5 38
 
5.8%
6 36
 
5.5%
7 34
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
D 2
22.2%
R 1
11.1%
L 1
11.1%
H 1
11.1%
E 1
11.1%
T 1
11.1%
K 1
11.1%
B 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
s 1
25.0%
u 1
25.0%
o 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 123
98.4%
. 2
 
1.6%
Space Separator
ValueCountFrequency (%)
617
100.0%
Open Punctuation
ValueCountFrequency (%)
( 122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2017
54.6%
Common 1662
45.0%
Latin 13
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
125
 
6.2%
115
 
5.7%
114
 
5.7%
113
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
Other values (101) 878
43.5%
Common
ValueCountFrequency (%)
617
37.1%
1 157
 
9.4%
, 123
 
7.4%
( 122
 
7.3%
) 122
 
7.3%
2 89
 
5.4%
4 78
 
4.7%
3 72
 
4.3%
0 69
 
4.2%
8 45
 
2.7%
Other values (6) 168
 
10.1%
Latin
ValueCountFrequency (%)
D 2
15.4%
R 1
7.7%
L 1
7.7%
e 1
7.7%
s 1
7.7%
H 1
7.7%
E 1
7.7%
u 1
7.7%
o 1
7.7%
T 1
7.7%
Other values (2) 2
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2017
54.6%
ASCII 1675
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
617
36.8%
1 157
 
9.4%
, 123
 
7.3%
( 122
 
7.3%
) 122
 
7.3%
2 89
 
5.3%
4 78
 
4.7%
3 72
 
4.3%
0 69
 
4.1%
8 45
 
2.7%
Other values (18) 181
 
10.8%
Hangul
ValueCountFrequency (%)
125
 
6.2%
115
 
5.7%
114
 
5.7%
113
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
112
 
5.6%
Other values (101) 878
43.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)58.6%
Missing41
Missing (%)27.0%
Infinite0
Infinite (%)0.0%
Mean1108.3333
Minimum1006
Maximum1235
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:52:38.445303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile1025.5
Q11062
median1097
Q31161
95-th percentile1222.5
Maximum1235
Range229
Interquartile range (IQR)99

Descriptive statistics

Standard deviation61.399487
Coefficient of variation (CV)0.055398033
Kurtosis-0.98919613
Mean1108.3333
Median Absolute Deviation (MAD)49
Skewness0.35716318
Sum123025
Variance3769.897
MonotonicityNot monotonic
2024-04-30T04:52:38.563411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1062 11
 
7.2%
1161 6
 
3.9%
1043 4
 
2.6%
1077 4
 
2.6%
1114 4
 
2.6%
1129 3
 
2.0%
1177 3
 
2.0%
1224 3
 
2.0%
1179 3
 
2.0%
1070 3
 
2.0%
Other values (55) 67
44.1%
(Missing) 41
27.0%
ValueCountFrequency (%)
1006 1
0.7%
1009 2
1.3%
1013 1
0.7%
1014 1
0.7%
1021 1
0.7%
1030 1
0.7%
1033 1
0.7%
1036 1
0.7%
1040 1
0.7%
1041 1
0.7%
ValueCountFrequency (%)
1235 1
 
0.7%
1233 1
 
0.7%
1226 1
 
0.7%
1224 3
2.0%
1221 1
 
0.7%
1214 1
 
0.7%
1209 2
1.3%
1204 1
 
0.7%
1179 3
2.0%
1178 1
 
0.7%
Distinct148
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:52:38.760415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length13
Mean length7.8289474
Min length2

Characters and Unicode

Total characters1190
Distinct characters235
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)94.7%

Sample

1st row코리아도시개발(주)
2nd row인덕종합관리(주)
3rd row우전종합개발
4th row(주)대공엔지니어링
5th row(주)장수종합개발
ValueCountFrequency (%)
주식회사 5
 
2.9%
3
 
1.7%
주)중앙앰에스 2
 
1.2%
주)대종기기산업 2
 
1.2%
금일환경 2
 
1.2%
덕산개발 2
 
1.2%
사회적협동조합 2
 
1.2%
클린 2
 
1.2%
캡틴크린 1
 
0.6%
주)아이비에스국제경호기획 1
 
0.6%
Other values (151) 151
87.3%
2024-04-30T04:52:39.044100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
 
8.1%
( 85
 
7.1%
) 85
 
7.1%
38
 
3.2%
29
 
2.4%
23
 
1.9%
22
 
1.8%
21
 
1.8%
21
 
1.8%
21
 
1.8%
Other values (225) 749
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 975
81.9%
Open Punctuation 85
 
7.1%
Close Punctuation 85
 
7.1%
Space Separator 21
 
1.8%
Uppercase Letter 16
 
1.3%
Decimal Number 3
 
0.3%
Other Punctuation 2
 
0.2%
Lowercase Letter 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
96
 
9.8%
38
 
3.9%
29
 
3.0%
23
 
2.4%
22
 
2.3%
21
 
2.2%
21
 
2.2%
21
 
2.2%
21
 
2.2%
20
 
2.1%
Other values (202) 663
68.0%
Uppercase Letter
ValueCountFrequency (%)
M 3
18.8%
G 2
12.5%
K 1
 
6.2%
O 1
 
6.2%
D 1
 
6.2%
I 1
 
6.2%
S 1
 
6.2%
J 1
 
6.2%
H 1
 
6.2%
C 1
 
6.2%
Other values (3) 3
18.8%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
6 1
33.3%
3 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
h 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 974
81.8%
Common 197
 
16.6%
Latin 18
 
1.5%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
96
 
9.9%
38
 
3.9%
29
 
3.0%
23
 
2.4%
22
 
2.3%
21
 
2.2%
21
 
2.2%
21
 
2.2%
21
 
2.2%
20
 
2.1%
Other values (201) 662
68.0%
Latin
ValueCountFrequency (%)
M 3
16.7%
G 2
 
11.1%
K 1
 
5.6%
O 1
 
5.6%
D 1
 
5.6%
I 1
 
5.6%
e 1
 
5.6%
h 1
 
5.6%
S 1
 
5.6%
J 1
 
5.6%
Other values (5) 5
27.8%
Common
ValueCountFrequency (%)
( 85
43.1%
) 85
43.1%
21
 
10.7%
. 2
 
1.0%
- 1
 
0.5%
5 1
 
0.5%
6 1
 
0.5%
3 1
 
0.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 974
81.8%
ASCII 215
 
18.1%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
96
 
9.9%
38
 
3.9%
29
 
3.0%
23
 
2.4%
22
 
2.3%
21
 
2.2%
21
 
2.2%
21
 
2.2%
21
 
2.2%
20
 
2.1%
Other values (201) 662
68.0%
ASCII
ValueCountFrequency (%)
( 85
39.5%
) 85
39.5%
21
 
9.8%
M 3
 
1.4%
. 2
 
0.9%
G 2
 
0.9%
K 1
 
0.5%
O 1
 
0.5%
D 1
 
0.5%
I 1
 
0.5%
Other values (13) 13
 
6.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct145
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2000-07-26 00:00:00
Maximum2024-02-29 11:26:28
2024-04-30T04:52:39.156049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:52:39.462109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
104 
U
48 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 104
68.4%
U 48
31.6%

Length

2024-04-30T04:52:39.566422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:39.647263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 104
68.4%
u 48
31.6%
Distinct64
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:02:00
2024-04-30T04:52:39.735012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:52:39.851859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
건물위생관리업
152 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건물위생관리업
2nd row건물위생관리업
3rd row건물위생관리업
4th row건물위생관리업
5th row건물위생관리업

Common Values

ValueCountFrequency (%)
건물위생관리업 152
100.0%

Length

2024-04-30T04:52:39.967546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:40.049681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 152
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)75.3%
Missing2
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean202058.58
Minimum200153.96
Maximum203648.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:52:40.166172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200153.96
5-th percentile201037.41
Q1201761.25
median202092.18
Q3202336.02
95-th percentile203184.7
Maximum203648.44
Range3494.4741
Interquartile range (IQR)574.7616

Descriptive statistics

Standard deviation610.74751
Coefficient of variation (CV)0.003022626
Kurtosis1.5654439
Mean202058.58
Median Absolute Deviation (MAD)301.20732
Skewness-0.067305596
Sum30308787
Variance373012.53
MonotonicityNot monotonic
2024-04-30T04:52:40.282894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202155.401317068 13
 
8.6%
202443.441398401 5
 
3.3%
201606.445832012 4
 
2.6%
201756.493628114 4
 
2.6%
201913.995856767 3
 
2.0%
203627.347902029 3
 
2.0%
201996.694547793 3
 
2.0%
201762.491162113 2
 
1.3%
202399.141092152 2
 
1.3%
202144.549823529 2
 
1.3%
Other values (103) 109
71.7%
ValueCountFrequency (%)
200153.963010668 2
1.3%
200542.427835442 1
0.7%
200550.98632709 1
0.7%
200768.087422005 1
0.7%
200902.806414022 1
0.7%
200913.604923265 1
0.7%
201028.710969406 1
0.7%
201048.037522189 1
0.7%
201101.299414088 1
0.7%
201160.290691198 1
0.7%
ValueCountFrequency (%)
203648.437133703 1
 
0.7%
203627.347902029 3
2.0%
203530.212455665 1
 
0.7%
203452.54250506 1
 
0.7%
203224.539337907 1
 
0.7%
203204.78676 1
 
0.7%
203160.153576134 1
 
0.7%
203072.524287403 1
 
0.7%
202949.357650112 1
 
0.7%
202914.612782425 1
 
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)75.3%
Missing2
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean458902.1
Minimum456454.26
Maximum461449.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:52:40.398875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456454.26
5-th percentile456948.24
Q1458080.77
median459137.6
Q3459754.67
95-th percentile460331.92
Maximum461449.07
Range4994.8111
Interquartile range (IQR)1673.8988

Descriptive statistics

Standard deviation1064.2276
Coefficient of variation (CV)0.0023190734
Kurtosis-0.58561458
Mean458902.1
Median Absolute Deviation (MAD)774.47351
Skewness-0.40336384
Sum68835315
Variance1132580.5
MonotonicityNot monotonic
2024-04-30T04:52:40.537032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459411.940883021 13
 
8.6%
457708.146944977 5
 
3.3%
460001.632075829 4
 
2.6%
459912.078374495 4
 
2.6%
459660.416218544 3
 
2.0%
458521.794917204 3
 
2.0%
459975.940915805 3
 
2.0%
459907.611510355 2
 
1.3%
457515.667690249 2
 
1.3%
458436.081912787 2
 
1.3%
Other values (103) 109
71.7%
ValueCountFrequency (%)
456454.262387278 1
0.7%
456516.997283985 1
0.7%
456553.934080847 1
0.7%
456614.805805491 1
0.7%
456636.308192293 1
0.7%
456888.586862568 1
0.7%
456894.547666667 1
0.7%
456943.819705953 1
0.7%
456953.650681144 1
0.7%
457154.744565393 1
0.7%
ValueCountFrequency (%)
461449.073521991 1
0.7%
461003.365591192 1
0.7%
460628.906771974 1
0.7%
460617.802817112 1
0.7%
460414.73336869 1
0.7%
460362.900002851 1
0.7%
460361.968255723 1
0.7%
460338.362856071 1
0.7%
460324.037639614 1
0.7%
460176.208450032 1
0.7%

위생업태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
건물위생관리업
124 
<NA>
28 

Length

Max length7
Median length7
Mean length6.4473684
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건물위생관리업
2nd row건물위생관리업
3rd row건물위생관리업
4th row건물위생관리업
5th row건물위생관리업

Common Values

ValueCountFrequency (%)
건물위생관리업 124
81.6%
<NA> 28
 
18.4%

Length

2024-04-30T04:52:40.644202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:40.746761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 124
81.6%
na 28
 
18.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)13.3%
Missing47
Missing (%)30.9%
Infinite0
Infinite (%)0.0%
Mean2.0380952
Minimum0
Maximum19
Zeros66
Zeros (%)43.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:52:40.825304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile10.8
Maximum19
Range19
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.028561
Coefficient of variation (CV)1.9766304
Kurtosis8.0566517
Mean2.0380952
Median Absolute Deviation (MAD)0
Skewness2.7926343
Sum214
Variance16.229304
MonotonicityNot monotonic
2024-04-30T04:52:40.916627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 66
43.4%
3 9
 
5.9%
2 7
 
4.6%
4 6
 
3.9%
5 5
 
3.3%
1 3
 
2.0%
19 2
 
1.3%
11 1
 
0.7%
7 1
 
0.7%
18 1
 
0.7%
Other values (4) 4
 
2.6%
(Missing) 47
30.9%
ValueCountFrequency (%)
0 66
43.4%
1 3
 
2.0%
2 7
 
4.6%
3 9
 
5.9%
4 6
 
3.9%
5 5
 
3.3%
7 1
 
0.7%
9 1
 
0.7%
10 1
 
0.7%
11 1
 
0.7%
ValueCountFrequency (%)
19 2
 
1.3%
18 1
 
0.7%
15 1
 
0.7%
13 1
 
0.7%
11 1
 
0.7%
10 1
 
0.7%
9 1
 
0.7%
7 1
 
0.7%
5 5
3.3%
4 6
3.9%
Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
72 
<NA>
52 
1
24 
6
 
3
4
 
1

Length

Max length4
Median length1
Mean length2.0263158
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 72
47.4%
<NA> 52
34.2%
1 24
 
15.8%
6 3
 
2.0%
4 1
 
0.7%

Length

2024-04-30T04:52:41.042316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:41.152963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 72
47.4%
na 52
34.2%
1 24
 
15.8%
6 3
 
2.0%
4 1
 
0.7%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)16.7%
Missing74
Missing (%)48.7%
Infinite0
Infinite (%)0.0%
Mean2.6794872
Minimum0
Maximum18
Zeros22
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:52:41.232105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile10
Maximum18
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.6979938
Coefficient of variation (CV)1.3801125
Kurtosis6.7597034
Mean2.6794872
Median Absolute Deviation (MAD)1
Skewness2.4938898
Sum209
Variance13.675158
MonotonicityNot monotonic
2024-04-30T04:52:41.320125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 22
 
14.5%
1 15
 
9.9%
2 14
 
9.2%
3 11
 
7.2%
4 5
 
3.3%
5 2
 
1.3%
10 2
 
1.3%
9 2
 
1.3%
7 1
 
0.7%
18 1
 
0.7%
Other values (3) 3
 
2.0%
(Missing) 74
48.7%
ValueCountFrequency (%)
0 22
14.5%
1 15
9.9%
2 14
9.2%
3 11
7.2%
4 5
 
3.3%
5 2
 
1.3%
7 1
 
0.7%
8 1
 
0.7%
9 2
 
1.3%
10 2
 
1.3%
ValueCountFrequency (%)
18 1
 
0.7%
17 1
 
0.7%
15 1
 
0.7%
10 2
 
1.3%
9 2
 
1.3%
8 1
 
0.7%
7 1
 
0.7%
5 2
 
1.3%
4 5
3.3%
3 11
7.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)20.6%
Missing89
Missing (%)58.6%
Infinite0
Infinite (%)0.0%
Mean2.952381
Minimum0
Maximum18
Zeros14
Zeros (%)9.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:52:41.408585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile10.9
Maximum18
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.9936586
Coefficient of variation (CV)1.3526908
Kurtosis5.4648029
Mean2.952381
Median Absolute Deviation (MAD)1
Skewness2.3474818
Sum186
Variance15.949309
MonotonicityNot monotonic
2024-04-30T04:52:41.499244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 15
 
9.9%
0 14
 
9.2%
2 12
 
7.9%
3 8
 
5.3%
4 4
 
2.6%
5 2
 
1.3%
10 2
 
1.3%
11 1
 
0.7%
7 1
 
0.7%
18 1
 
0.7%
Other values (3) 3
 
2.0%
(Missing) 89
58.6%
ValueCountFrequency (%)
0 14
9.2%
1 15
9.9%
2 12
7.9%
3 8
5.3%
4 4
 
2.6%
5 2
 
1.3%
7 1
 
0.7%
9 1
 
0.7%
10 2
 
1.3%
11 1
 
0.7%
ValueCountFrequency (%)
18 1
 
0.7%
17 1
 
0.7%
15 1
 
0.7%
11 1
 
0.7%
10 2
 
1.3%
9 1
 
0.7%
7 1
 
0.7%
5 2
 
1.3%
4 4
2.6%
3 8
5.3%
Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
103 
0
41 
1
 
8

Length

Max length4
Median length4
Mean length3.0328947
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 103
67.8%
0 41
 
27.0%
1 8
 
5.3%

Length

2024-04-30T04:52:41.606798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:41.695939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 103
67.8%
0 41
 
27.0%
1 8
 
5.3%
Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
113 
0
31 
1
 
8

Length

Max length4
Median length4
Mean length3.2302632
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 113
74.3%
0 31
 
20.4%
1 8
 
5.3%

Length

2024-04-30T04:52:41.781634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:41.868478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
74.3%
0 31
 
20.4%
1 8
 
5.3%

한실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
84 
<NA>
68 

Length

Max length4
Median length1
Mean length2.3421053
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 84
55.3%
<NA> 68
44.7%

Length

2024-04-30T04:52:41.962985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:42.051334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 84
55.3%
na 68
44.7%

양실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
84 
<NA>
68 

Length

Max length4
Median length1
Mean length2.3421053
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 84
55.3%
<NA> 68
44.7%

Length

2024-04-30T04:52:42.145884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:42.255658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 84
55.3%
na 68
44.7%

욕실수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
84 
<NA>
68 

Length

Max length4
Median length1
Mean length2.3421053
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 84
55.3%
<NA> 68
44.7%

Length

2024-04-30T04:52:42.353688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:42.441798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 84
55.3%
na 68
44.7%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing34
Missing (%)22.4%
Memory size436.0 B
False
118 
(Missing)
34 
ValueCountFrequency (%)
False 118
77.6%
(Missing) 34
 
22.4%
2024-04-30T04:52:42.508265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
84 
<NA>
68 

Length

Max length4
Median length1
Mean length2.3421053
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 84
55.3%
<NA> 68
44.7%

Length

2024-04-30T04:52:42.587467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:42.668132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 84
55.3%
na 68
44.7%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
124 
임대
27 
자가
 
1

Length

Max length4
Median length4
Mean length3.6315789
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 124
81.6%
임대 27
 
17.8%
자가 1
 
0.7%

Length

2024-04-30T04:52:42.758856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:42.852546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 124
81.6%
임대 27
 
17.8%
자가 1
 
0.7%

세탁기수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
78 
0
74 

Length

Max length4
Median length4
Mean length2.5394737
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 78
51.3%
0 74
48.7%

Length

2024-04-30T04:52:42.939155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:43.019988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
51.3%
0 74
48.7%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
120 
0
31 
1
 
1

Length

Max length4
Median length4
Mean length3.3684211
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 120
78.9%
0 31
 
20.4%
1 1
 
0.7%

Length

2024-04-30T04:52:43.122491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:43.227285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 120
78.9%
0 31
 
20.4%
1 1
 
0.7%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
120 
0
30 
27
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.375
Min length1

Unique

Unique2 ?
Unique (%)1.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 120
78.9%
0 30
 
19.7%
27 1
 
0.7%
1 1
 
0.7%

Length

2024-04-30T04:52:43.326499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:43.429967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 120
78.9%
0 30
 
19.7%
27 1
 
0.7%
1 1
 
0.7%

회수건조수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
83 
0
69 

Length

Max length4
Median length4
Mean length2.6381579
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 83
54.6%
0 69
45.4%

Length

2024-04-30T04:52:43.523885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:43.605721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 83
54.6%
0 69
45.4%

침대수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
86 
0
66 

Length

Max length4
Median length4
Mean length2.6973684
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 86
56.6%
0 66
43.4%

Length

2024-04-30T04:52:43.697772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:52:43.778630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 86
56.6%
0 66
43.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing28
Missing (%)18.4%
Memory size436.0 B
False
124 
(Missing)
28 
ValueCountFrequency (%)
False 124
81.6%
(Missing) 28
 
18.4%
2024-04-30T04:52:43.848456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030800003080000-206-1992-0209319920221<NA>3폐업2폐업20031101<NA><NA><NA>02 9989100.00142877서울특별시 강북구 수유동 205-0 수유벽산 B동상가 110호<NA><NA>코리아도시개발(주)2004-03-04 00:00:00I2018-08-31 23:59:59.0건물위생관리업201606.445832460001.632076건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130800003080000-206-1995-0209419950615<NA>3폐업2폐업20100512<NA><NA><NA>02 984984085.00142803서울특별시 강북구 미아동 189-14 (도봉로 258)<NA><NA>인덕종합관리(주)2008-10-28 15:45:19I2018-08-31 23:59:59.0건물위생관리업202092.181818458818.034104건물위생관리업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230800003080000-206-1995-0209519950725<NA>3폐업2폐업20020524<NA><NA><NA>02 9336856.00142867서울특별시 강북구 번동 446-13<NA><NA>우전종합개발2002-05-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업202155.401317459411.940883건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330800003080000-206-1995-0209619950822<NA>3폐업2폐업20120302<NA><NA><NA>02 9972391110.00142864서울특별시 강북구 번동 415-19 (오패산길 400)서울특별시 강북구 오패산로 396-1 (번동,(오패산길 400))1064(주)대공엔지니어링2008-04-30 17:50:16I2018-08-31 23:59:59.0건물위생관리업202387.637187459370.392167건물위생관리업2<NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430800003080000-206-1995-0209719950906<NA>3폐업2폐업19961104<NA><NA><NA>02 9888384.00142886서울특별시 강북구 수유동 472-510<NA><NA>(주)장수종합개발2001-09-26 00:00:00I2018-08-31 23:59:59.0건물위생관리업201570.134107458926.757273건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530800003080000-206-1995-0209819951201<NA>3폐업2폐업19961030<NA><NA><NA>02 9903402.00142867서울특별시 강북구 번동 446-13<NA><NA>온아종합용역(주)2001-09-26 00:00:00I2018-08-31 23:59:59.0건물위생관리업202155.401317459411.940883건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630800003080000-206-1996-0209919960306<NA>3폐업2폐업20020504<NA><NA><NA>02 907861256.00142891서울특별시 강북구 수유동 46-54<NA><NA>가든실업2002-05-27 00:00:00I2018-08-31 23:59:59.0건물위생관리업201763.012723459194.347949건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730800003080000-206-1997-0210019970908<NA>3폐업2폐업19980731<NA><NA><NA>02 9851322126.02142803서울특별시 강북구 미아동 197-16<NA><NA>청안공사2001-09-26 00:00:00I2018-08-31 23:59:59.0건물위생관리업202267.110684458302.905538건물위생관리업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830800003080000-206-1997-021021997-12-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 906224636.90142-867서울특별시 강북구 번동 446-13 가든타워 1319호서울특별시 강북구 도봉로 328, 1319호 (번동, 가든타워)1062(주)태경종합개발2024-02-14 16:06:23U2023-12-01 23:06:00.0건물위생관리업202155.401317459411.940883<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
930800003080000-206-1997-0210319971105<NA>3폐업2폐업20220919<NA><NA><NA>02 9860441132.00142803서울특별시 강북구 미아동 189-14 403호, 운산빌딩서울특별시 강북구 도봉로 260 (미아동, 403호, 운산빌딩)1132(주) 화평2022-09-19 17:05:24U2021-12-08 22:01:00.0건물위생관리업202092.181818458818.034104<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
14230800003080000-206-2022-000072022-10-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.72142-863서울특별시 강북구 번동 237 번동주공상가아파트 301동 지하14호서울특별시 강북구 오현로 208, 301동 지하층 14호 (번동, 번동주공아파트)1224미우2023-10-16 16:59:34U2022-10-30 23:08:00.0건물위생관리업203627.347902458521.794917<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14330800003080000-206-2022-0000820221031<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30142809서울특별시 강북구 미아동 131-6서울특별시 강북구 도봉로 144, 4층 D-108호 (미아동)1161글로리아2022-10-31 17:43:53I2021-11-01 00:02:00.0건물위생관리업202443.441398457708.146945<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14430800003080000-206-2022-000092022-07-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.47142-868서울특별시 강북구 번동 465-4 밀레니엄 오피스텔 501호서울특별시 강북구 도봉로 396, 밀레니엄 오피스텔 5층 501호 (번동)1056(주)리치몽골2023-07-17 09:20:52I2022-12-06 23:09:00.0건물위생관리업202586.367374459936.761771<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14530800003080000-206-2023-000012023-02-06<NA>3폐업2폐업2023-08-09<NA><NA><NA><NA>100.00142-810서울특별시 강북구 미아동 217-84 지하1층서울특별시 강북구 솔매로43길 96, 지하1층 (미아동)1118(주)조이씨엠에스2023-08-09 10:07:11U2022-12-07 23:01:00.0건물위생관리업201948.347749458618.594476<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14630800003080000-206-2023-000022023-08-17<NA>1영업/정상1영업<NA><NA><NA><NA>02 989 113223.00142-816서울특별시 강북구 미아동 380-37 1층서울특별시 강북구 솔샘로59가길 2, 1층 (미아동)1178제이앤이시스템2023-08-17 10:01:26I2022-12-07 23:09:00.0건물위생관리업202156.063938457352.575762<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14730800003080000-206-2023-000032023-08-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00142-803서울특별시 강북구 미아동 165-8 내안에 House 1층서울특별시 강북구 덕릉로30길 42, 내안에 House 1층 (미아동)1132초록나무2023-08-17 14:04:29I2022-12-07 23:09:00.0건물위생관리업202178.92597458945.174876<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14830800003080000-206-2023-000042023-08-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.00142-876서울특별시 강북구 수유동 181-40 신성자동차공업사 1층서울특별시 강북구 한천로150길 20, 신성자동차공업사 1층 (수유동)1053종합건물관리쉬작She作2024-01-24 17:11:39U2023-11-30 22:06:00.0건물위생관리업202021.254583460118.308378<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14930800003080000-206-2024-000012024-01-17<NA>1영업/정상1영업<NA><NA><NA><NA>02 719945164.56142-800서울특별시 강북구 미아동 77-16서울특별시 강북구 오패산로 148, 1층 (미아동)1233(주)동행2024-01-17 13:50:10I2023-11-30 23:09:00.0건물위생관리업202914.612782456953.650681<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15030800003080000-206-2024-000022024-02-21<NA>1영업/정상1영업<NA><NA><NA><NA>02 906 224636.90142-867서울특별시 강북구 번동 446-13 가든타워빌딩 11층 1117호서울특별시 강북구 도봉로 328, 가든타워빌딩 11층 1117호 (번동)1062태경종합관리2024-02-21 14:01:43I2023-12-01 22:03:00.0건물위생관리업202155.401317459411.940883<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15130800003080000-206-2024-000032024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.10142-874서울특별시 강북구 수유동 50-57 1층서울특별시 강북구 삼양로80나길 68, 1층 (수유동)1114사회적협동조합 행복모아2024-02-29 11:26:28I2023-12-03 00:02:00.0건물위생관리업201776.330664459051.606792<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>